Abstract: Data visualization is fundamental to the data science process. Using plots and graphs to convey a complex idea makes your data more accessible to everyone. In this session, you will learn the fundamentals of plotting with Pandas in Jupyter by building an interactive visualization prototype that can also run as a standalone web application/dashboard. This session is for anyone who wants to be more familiar with data visualization, hands-on, with Python, Pandas, Matplotlib, interactive widgets, and Flask.
At the end of this session, attendees will:
- Be familiar with everyday notebook and data visualization conventions
- Be able to describe the integration between matplotlib is integrated with Pandas
- Understand the concept of "figure" and "axes."
- Implement standard plots using Pandas
- Understand the Juptyer plugin system
- Install and configure "widgets."
- Implement a basic prototype visualization for exploring data with interactive elements
- Be familiar with other visual frameworks and assess their strengths
- Understand the tradeoffs between sharing notebooks vs. custom dashboards
- Be able to identify the anatomy of a Flask web application
- Implement a prototype visualization from Jupyter, in Flask
Python, Pandas, bash shell/command-line familiarity.
Bio: At the age of 8, David began learning the BASIC programming language while living in the outskirts of Alaska. He studied music performance but found the beginning of his career building a small software and consulting company in the late 90's. David’s career spans almost 20 years including many startups as a lead engineer, building scalable data services from prototype to production. During his time at Sony/Gracenote, leading the development of a handful of prototypes were featured multiple years in the Consumer Electronics Show, spanning problems with recommender systems, content classification, and profiling type problems. More recently, David was a data scientist at a YC backed dating app company researching and building scalable recommendation pipelines.
Currently, David works at General Assembly as a Global Data Science Instructor, where he helped architect the first version of the data science immersive curriculum and pilot many new programs developed internally. Regularly delivering lectures in a hybrid format classroom on topics ranging from engineering, statistics, and ML.